化学空间可视化：将多维化学空间转化为基于相似性的分子网络。
Chemical space visualization: transforming multidimensional chemical spaces into similarity-based molecular networks.
作者信息
de la Vega de León Antonio, Bajorath Jürgen
机构信息
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany.
出版信息
Future Med Chem. 2016 Sep;8(14):1769-78. doi: 10.4155/fmc-2016-0023. Epub 2016 Aug 30.
BACKGROUND
The concept of chemical space is of fundamental relevance for medicinal chemistry and chemical informatics. Multidimensional chemical space representations are coordinate-based. Chemical space networks (CSNs) have been introduced as a coordinate-free representation.
RESULTS
A computational approach is presented for the transformation of multidimensional chemical space into CSNs. The design of transformation CSNs (TRANS-CSNs) is based upon a similarity function that directly reflects distance relationships in original multidimensional space.
CONCLUSION
TRANS-CSNs provide an immediate visualization of coordinate-based chemical space and do not require the use of dimensionality reduction techniques. At low network density, TRANS-CSNs are readily interpretable and make it possible to evaluate structure-activity relationship information originating from multidimensional chemical space.
背景
化学空间的概念对药物化学和化学信息学具有根本重要性。多维化学空间表示是基于坐标的。化学空间网络（CSN）已作为一种无坐标表示被引入。
结果
提出了一种将多维化学空间转换为CSN的计算方法。转换化学空间网络（TRANS-CSN）的设计基于一个直接反映原始多维空间中距离关系的相似性函数。
结论
TRANS-CSN提供了基于坐标的化学空间的直接可视化，并且不需要使用降维技术。在低网络密度下，TRANS-CSN易于解释，并使得评估源自多维化学空间的构效关系信息成为可能。
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